Knowledge represented by mathematical models for fault diagnosis in chemical processing units

摘要

The automation of fault diagnos in the field of chemical processing has been thwarted, in the past, chiefly by the inability to represent quantitative causal models and process constraints. This paper describes a system which uses mathematical model-based reasoning for fault diagnosis in a chemical plant. This approach appears to give somewhat better results in comparison with past attempts at using expert systems, which typically carried out the diagnosis on the basis of empirical knowledge alone. The latter systems usually suffer from the disadvantage of being too process-specific, inflexible and cumbersome.